Search Results (554)

With the increase in the demand for electronic-grade high-purity silane in the semiconductor chip industry, it is of great significance to develop a green and economical method for silane production. Therefore, a novel energy-saving fixed-bed process was proposed innovatively. In this paper, the thermodynamics and kinetics of the trichlorosilane disproportionation system were studied, and the optimal reaction conditions for the resin catalyst were determined, which were used for the subsequent simulation. Based on the conventional DR1 + DR2 process (which includes one trichlorosilane disproportionation reactor (DR1) and one dichlorosilane disproportionation reactor (DR2)), by adding an additional disproportionation reactor to the TCS recycle loop and/or DCS recycle loop, three improved process configurations were designed, including 2DR1 + DR2, DR1 + 2DR2, and 2DR1 + 2DR2 processes. Then, combined with four-column heat integration, the HI + 2DR1 + 2DR2 process was proposed to solve the bottleneck problems of high energy consumption and large circulation flow rate. The results show that the HI + 2DR1 + 2DR2 process achieved the best energy-saving effect. The TCS recycle loop flow rate reduced by 36.87%, the DCS recycle loop flow rate reduced by 12.41%, total energy consumption decreased by 62.8%, and CO₂ emissions decreased by 56.72%. The unit energy consumption is 13.8 kg steam/kg SiH₄, and the silane purity is greater than 99.9999%. This design can be easily applied to the existing production process of the silane plant, achieving energy-saving and low-cost production of silane. Full article

Diffuse pollution from agricultural runoff, characterized by intermittent discharges of complex contaminant mixtures, including nutrients, pesticides, and heavy metals (HMs), poses a persistent threat to global water quality. Conventional “end-of-pipe” strategies often fail to address these decentralized, nonpoint sources. This review examines the evolution of Permeable Reactive Barriers (PRBs) from static, abiotic filters into modern Permeable Reactive Bio-Barriers (PRBBs), engineered as dynamic, fixed-bed biofilm reactors. A key advancement in PRBB efficacy is the exploitation of biofilm plasticity, particularly in response to coexistence with organic and inorganic pollutants. While heavy metals are traditionally viewed as inhibitors, this review synthesizes evidence showing that subinhibitory HM levels can act as structural and functional drivers. These metals induce the upregulation of Extracellular Polymeric Substances (EPSs), creating a “protective shield” that sequesters metals and confers functional resilience on the microbial consortia responsible for nutrient removal and pesticide biodegradation. The review analyzes contaminant removal mechanisms, highlighting the bio-chemo synergy between reactive media and biofilms, and proposes a classification framework based on target contaminants, media, and technological integration. Significant focus is placed on emerging hybrid multi-media systems designed to protect the microbial community from toxic metal shocks, alongside the integration of artificial intelligence for predictive control. While challenges in hydraulic sustainability and field validation remain, PRBBs represent a compact, low-energy, and scalable ecotechnology. PRBBs offer a strategically targeted solution within the Nature-Based Solutions toolkit for building resilient protection of aquatic ecosystems at the critical land-water interface. Full article

Sulfur-mediated autotrophic denitrification (SAD) is an innovative and sustainable water treatment technology, which operates without an external carbon source and achieves lower sludge production. Firstly, this review provides a detailed examination of sulfur-based fillers, encompassing their respective types, preparation methods, advantages and drawbacks. Subsequently, it reviews the mainstream functional microbial communities across various process stages, such as Thiobacillus, Sulfurimonas, and Ignavibacterium. Moreover, the process characteristics of mainstream SAD reactor types, such as fluidized bed, fixed bed, and moving bed biofilm reactors, are reviewed, and the effects of key process parameters like pH, temperature, and dissolved oxygen on treatment efficiencies are further analyzed. Additionally, the applications cases of SAD in advanced wastewater treatment, river remediation, wetland restoration, and groundwater purification are summarized, demonstrating its broad and diverse application potential in environmental engineering. Finally, key challenges of SAD are identified, including the complexity of microbial metabolic interactions, the accumulation of intermediate products, and the need for improved fillers and reactor configurations. Future research priorities are discussed in three areas: microbial community regulation, control and utilization of intermediate products, and development of advanced fillers and reactor configurations. Overall, this review integrates key technical parameters and operational experience of SAD, providing a consolidated reference for researchers and practitioners interested in the development and application of this technology. Full article

CuCo-based catalysts are promising candidates for higher alcohol synthesis from syngas, yet their performance is often limited by poor metal dispersion and insufficient Cu-Co synergy. In this work, a series of ordered mesoporous CuCoAl catalysts with varying Cu/Co atomic ratios were synthesized via the evaporation-induced self-assembly (EISA) method. The structural, electronic, and catalytic properties were systematically investigated using N₂ physisorption, XRD, TEM, H₂-TPR, CO-TPD, XPS, and fixed-bed reactor evaluation. The results show that all CuCoAl catalysts prepared by the EISA method possess well-ordered mesoporous structures with high surface areas (up to 235 m²/g) and narrow pore size distributions. The interaction between Cu and Co stabilizes the mesoporous framework, inhibits Cu particle growth, and induces electron transfer from Cu to Co as evidenced by XPS. Among the catalysts tested, Cu₁Co₁Al (Cu/Co = 1:1) exhibits the highest strong CO adsorption capacity (1.54 mmol/g) and surface hydroxyl content (63.29%), achieving a CO conversion of 32.9% with a C₂⁺ alcohol space–time yield of 20.5 mg·gcat⁻¹·h⁻¹. These findings establish clear structure–performance relationships for ordered mesoporous CuCoAl catalysts and provide fundamental guidance for the rational design of efficient catalysts for higher alcohol synthesis. Full article

The improper disposal of end-of-life tires poses significant environmental challenges due to their petroleum-based composition and slow degradation, while simultaneously representing an underutilized energy resource. This study investigates the slow pyrolysis of shredded waste tires in a fixed-bed electrically heated reactor to evaluate the production and fuel properties of gaseous, liquid, and solid fractions. Experiments were conducted with 100 g samples under nitrogen at final temperatures of 400, 500, and 600 °C, with residence times of 40, 25, and 10 min, respectively. Higher temperatures promoted gas formation, increasing yields from 27% to 32% and achieving a maximum lower heating value of 30.54 MJ m⁻³ at 600 °C, with enhanced H₂ and CH₄ contents. Solid yields decreased slightly (41% to 37%), while char maintained stable heating values (~29 MJ kg⁻¹). Liquid yields remained near 33% and showed high calorific values (~41 MJ kg⁻¹), densities of 700–770 kg m⁻³, low acidity, low ash content, and increased viscosity at higher temperatures. Energy conversion efficiency reached 74.4% at 500 °C. The integrated evaluation of all fractions under identical conditions highlights fixed-bed pyrolysis as a promising pathway for waste-tire valorization and decentralized fuel production. Full article

The catalytic upgrading of vacuum residue (VR) is constrained by the high cost, diffusional limitations, and rapid deactivation of conventional zeolite-based catalysts due to severe coking. Addressing this, we developed novel, low-cost, and coke-resistant catalysts utilizing naturally abundant Iraqi kaolin. A composite support comprising 80 wt.% Iraqi red kaolin and 20 wt.% white kaolin was synthesized via thermal activation at 800 °C and acid leaching. This support was subsequently impregnated with transition and rare-earth metals (Ni, Co, Ce) at 3–40 wt.% loadings, and comprehensively characterized using XRD, BET, SEM-EDX, and XPS. Catalytic performance was evaluated during VR upgrading in a fixed-bed batch reactor at 450 °C. Among the formulations, the 20 wt.% Ce-loaded catalyst (MKRW-800A@Ce20%) exhibited superior efficiency, achieving 80.15% VR conversion, 61.04% liquid yield, and minimal coke formation (3.81 g) compared to Ni and Co counterparts. This enhanced activity is attributed to synergistic effects of improved surface acidity, textural accessibility, and the Ce³⁺/Ce⁴⁺ redox couple, which promotes selective cracking while suppressing coke precursors. These findings provide new insights into the rational design of natural clay-based catalysts, establishing Ce-modified metakaolin as a viable, sustainable alternative to zeolites for industrial heavy-oil processing. Full article

In this study, supervised machine learning (ML) regression models are employed to predict water uptake during the sorption process in a sorption reactor for thermal energy storage applications. Two main methods are used to study sorption storage systems: experimental studies and numerical simulations. Experimental studies involve physical testing and measurements but are often costly and time-consuming. Numerical simulations are more flexible and cost-effective, though they can require significant computational resources for large or complex systems. To address these challenges, researchers are increasingly employing various machine learning techniques, which offer strong potential for data analysis and predictive modeling. In this study, CFD-based sorption simulations are integrated with machine learning models to predict the spatiotemporal evolution of water uptake. Several ML techniques including support vector regression (SVR), Random Forest, XGBoost, CatBoost (gradient boosting decision trees), and multilayer perceptron neural networks (MLPs) are evaluated and compared. A fixed-bed reactor equipped with fins and tubes is considered within a closed adsorption thermal storage system. Numerical simulations are conducted for three different fin lengths (10 mm, 25 mm, and 35 mm) to generate a comprehensive dataset for training the ML models and capturing the complex temporal evolution of water uptake, thereby enabling predictions for unseen fin geometries. The results indicate that neural network-based models achieve superior predictive performance compared to the other methods. For water uptake training, the mean absolute error (MAE), root mean squared error (RMSE), and coefficient of determination $\left(R^2\right)$ are approximately 2.83, 4.37, and 0.91, respectively. The predicted water uptake shows close agreement with the numerical simulation results. For the prediction cases, the MAE, MSE, and $R^2$ values are approximately 1.13, 1.2, and 0.8, respectively. Overall, the study demonstrates that machine learning models can accurately predict water uptake beyond the training dataset, indicating strong generalization capability and significant potential for improving thermal management system design. Additionally, the proposed approach reduces simulation time and computational cost while providing an efficient and reliable framework for modeling complex sorption processes in thermal energy storage systems. Full article

Driven by the growing global energy demand and the pursuit of carbon utilization goals, dry reforming of methane (DRM) has attracted considerable attention for its ability to convert CO₂ and CH₄ into syngas. Biogas, an eco-friendly product of processes such as anaerobic digestion, is primarily composed of CO₂ and CH₄ and ideally meets the feedstock requirements for DRM. In practice, biogas is generated via anaerobic digestion of livestock manure and other organic waste, providing a stable and sustainable source for the DRM reaction and thus enabling waste valorization. Supported Ni⁰ catalysts have become a research focus in this field due to their high catalytic activity and moderate cost. Conventional particulate Ni⁰ catalysts, however, are prone to carbon coking in fixed-bed applications and are difficult to effectively recover and regenerate after the reaction; thus, they are often being discarded, leading to resource waste and environmental burden. To address these issues, this study has designed a novel metal-sintered fleece catalyst support and developed a corresponding reactor. The effects of the catalyst preparation method, activation conditions, and the support structure on DRM performance have been systematically investigated. The spent Ni-based catalyst could be regenerated via calcination to restore catalytic activity and enable multiple cycles of use, significantly extending the catalyst’s lifespan and offering both economic and environmental benefits. Experimental results have demonstrated that the reactor achieved a conversion rate exceeding 80% with near-complete product selectivity. Full article

Coke, as an essential metallurgical raw material, is widely used in iron and steel production. To investigate the pyrolysis behavior and cross-linking reactions during the pyrolysis of coking coal, pyrolysis experiments were conducted in a quartz-tube fixed-bed reactor placed in an electric furnace. The yields and compositions of the pyrolysis products were systematically analyzed. Gaseous and tar components generated at different pyrolysis stages were characterized using gas chromatography (GC) and gas chromatography–mass spectrometry (GC–MS). The semi-coke was examined by X-ray photoelectron spectroscopy (XPS) and scanning electron microscopy (SEM). The results indicated that the yields of tar from coking coal pyrolysis have a notable impact on the cross-linking reactions occurring during the coal pyrolysis process. The structural differences between Malan coal (ML) and Tunlan coal (TL) coals underlie their distinct behaviors in cross-linking intensity, tar evolution profiles, and coke-forming properties. For high-volatile, highly fluid ML coal, the release of the aliphatic compounds in tar volatiles remains relatively low at the temperature of maximum fluidity, which is beneficial to the cross-linking reactions. In contrast, for TL coal with lower volatility and fluidity, substantial H₂ emission during the early pyrolysis stage promotes cross-linking reactions. This study provides new insights into the temperature-dependent evolution of cross-linking reactions during coking coal pyrolysis. Full article

The selective transformation of biomass-derived feedstocks into value-added chemicals via targeted C-O bond cleavage remains challenging due to the presence of multiple reducible bonds and typically low catalytic selectivity. Herein, we report a robust non-noble metal CoCe catalyst for the selective ring-opening hydrogenolysis of 2-furoic acid (2-FA), an industrialized biomass-derived platform molecule, to 5-hydroxypentanoic acid (5-HVA) and its derivatives, which have potential applications as fuel additives. The optimized 90CoCe catalyst with inverse phase demonstrates superior catalytic performance, achieving a total yield of more than 85% for 5-HVA and its derivatives under mild reaction conditions (130 °C, 2 MPa H₂). Extensive characterizations reveal that the inverse-phase 90CoCe catalyst possesses abundant oxygen vacancies at the Co-CeO_x interface, with the formation of Co-Ov-Ce interfacial species. The interfacial Co-Ov-Ce sites serve as specific adsorption centers for the 2-FA molecule, orienting it into a titled adsorption configuration that is highly favorable for the C₂-O₁ bond cleavage in the furan ring. Meanwhile, adjacent Co⁰ sites efficiently dissociate hydrogen into active hydrogen species for the hydrogenolysis of the C₂-O₁ bond to form ring-opening products. The synergistic balance between the hydrogenation Co⁰ sites and the interfacial Co-Ov-Ce adsorption sites is crucial to the high catalytic activity and selectivity of the CoCe catalyst. Moreover, the 90CoCe catalyst maintains stable catalytic performance during a 40 h continuous test in a fixed-bed reactor, demonstrating its great potential for industrial applications. Full article

Gas-phase oxidation of volatile organic compounds (VOCs) with the aid of ozone can be an attractive, energy-efficient way of treating exhaust gas streams in a low-temperature process, enabling the sustainable operation of industrial installations in a natural environment. This work is focused on the efficiency and kinetics of toluene oxidation with ozone towards CO₂ and H₂O in the presence of a SiO₂-supported cobalt catalyst. A kinetic model is proposed based on a simplified reaction mechanism, with the parameters determined from measurements carried out in a fixed-bed reactor at 40–65 °C under conditions ensuring negligible mass transfer resistance. The proposed model provided satisfactory agreement between the predicted and measured toluene and ozone conversion rates and the formation rate of CO₂, as well as in conditions when mass transfer resistance due to internal diffusion in the catalyst pellet was necessary to consider. The discussed results provide an assessment of the space velocity and ozone usage necessary to achieve a given degree of toluene conversion and mineralization to CO₂. The proposed model can be used for the design of a sustainable, low-temperature ozone-assisted catalytic process of VOC abatement. Full article

Methanol ammoxidation over FeMo/SiO₂ has emerged as a promising low-temperature route to hydrogen cyanide (HCN). In this work, an eight-parameter Mars–van Krevelen (MvK) kinetic model, previously established from intrinsic fixed-bed experiments, is embedded in a heterogeneous plug-flow description to design an industrial multitubular reactor with a nominal HCN capacity of 10,000 t∙a⁻¹. The reactor is represented by a bank of isothermal tubes that are operated at 420 °C and a mildly elevated pressure, each packed with spherical FeMo/SiO₂ pellets. Detailed simulations for a 30 mm inner tube diameter and 2 mm pellets, including an Ergun pressure drop and intraparticle diffusion with realistic effective diffusivities, show that a 4 m bed at an outlet pressure of 1.5 bar (abs) achieves an essentially complete methanol conversion with a carbon-based HCN yield of ≈0.95 at a space time of ≈160 gcat∙h∙mol⁻¹. Axial effectiveness factors remain above ≈0.6, indicating moderate but manageable diffusion limitations. Comparison with a 35 mm/3 mm geometry reveals a clear trade-off between pressure drop and HCN selectivity. Parametric studies of space time, feed composition and outlet pressure delineate a broad non-flammable operating window with robust HCN yield and moderate compression duty. The results demonstrate how a mechanistic MvK rate expression can be translated into a practical design framework for FeMo-based multitubular HCN reactors. Full article

The increasing demand for sustainable materials has driven interest in biocomposites that incorporate low-value agricultural residues to offset the use of virgin plastics. The study investigated the production of blend pellets from raw and torrefied almond shells and post-consumer plastic waste as a potential feedstock for biocomposite and biofuels applications. Almond shells were torrefied in a lab-scale fixed-bed reactor at 300 °C for 30 min prior to the pelleting tests. High-density polyethylene (HDPE) and polypropylene (PP) wastes were size-reduced in a Crumbler (rotary shear grinder) fitted with a 2 mm head and a 2 mm screen to remove the fines. A portion of the crumbled HDPE, and torrefied almond shells were further ground in a Wiley mill fitted with 2 and 1 mm screens for flat die pelleting tests. The flat die pellet mill used for testing had a 6 mm die and a length-to-diameter (L/D) ratio of 2.0. The blend ratio consisted of 30% torrefied almond shells and 70% HDPE, with a 10% starch binder. The measured pellet properties include unit, bulk and tap densities, durability, and expansion ratio. The bulk density of the blend pellets ranged from 360 to 410 kg/m³, and durability ranged from 80% to 88%. The blend pellet unit density ranged from 830 to 880 kg/m³. The blend pellets produced using crumbled HDPE, PP and raw and torrefied almond shells in a ring die pilot-scale pellet mill with an L/D ratio of 6 and steam conditioning exhibit similar densities to those of HDPE pellets produced using a flat die pellet mill, albeit with lower durability. The study indicated that a smaller grind size and preheating the blend before pelleting produce blend pellets with higher density and greater durability. Full article

This work presents a comprehensive analysis of reactor modeling studies for the methanation of CO_x, with the aim of identifying trends, evaluating modeling strategies, and suggesting a generalized modeling framework. The analysis spans a wide range of configurations, including packed/fixed-bed reactors (immobilized catalyst pellets/particles), fluidized-bed reactors, and structured catalyst reactors, as well as membrane and slurry/bubble-column configurations when applicable. This highlights the diversity of modeling approaches used, ranging from simple 1D pseudo-homogeneous models to complex 2D heterogeneous simulations. Emphasis is placed on the governing assumptions, dimensional formulations, transport phenomena, and kinetic models employed across studies. By systematically comparing these models, this work identifies the most critical modeling assumptions and parameters that govern the prediction reliability of reactor performance (e.g., conversion and temperature profiles) and inform reactor design. The proposed reactor model integrates insights from the literature, balancing model fidelity and computational feasibility, and serves as a foundational tool for future modeling efforts and industrial applications. This work contributes to the field by offering a unified perspective that links model complexity to physical realism, providing valuable guidance in the development of predictive tools for CO_x methanation systems. Full article

The catalytic conversion of carbon dioxide to methanol is significantly important both practically and scientifically for the reduction in CO₂ emissions. Furthermore, it can partially address the issue of human reliance on non-renewable resources. The main motivation of this study is to use a melamine polymer network to support a copper-based catalyst for CO₂ hydrogenation to methanol. Based on Schiff base chemistry, a facile catalyst-free process, a novel porous polyaminal polymer (MGPN) was prepared with nitrogen contents as high as 38%. MGPN was used as a support for Cu-based catalyst and applied in CO₂ hydrogenation to CH₃OH under mild conditions. A deep characterization of the MGPN@CuO/ZnO/Al₂O₃ catalyst was made through FTIR, N₂ adsorption–desorption, SEM-EDS, TEM, TGA, XRD, CO₂-TPD, and H₂-TPR techniques. The CO₂ hydrogenation study was performed in a fixed bed reactor with a residence time of 1.104 s on varying parameters such as the metal loading, catalyst amount, flow rate, pressure, calcination temperatures, reduction temperatures, and catalytic reaction temperature profile. The space-time yield (STY) of 145.43 mg_methanol·g_catalyst⁻¹·h⁻¹, a selectivity of 98.36%, and CO₂ conversion of 11.76% were obtained under an economically and energetically sustainable low-pressure (1 MPa) and 260 °C hydrogenation process. Full article